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Article

Validation of Variant Assembly Using HAPHPIPE with Next-Generation Sequence Data from Viruses

1
Computational Biology Institute, Milken Institute School of Public Health, The George Washington University, Washington, DC 20052, USA
2
Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC 20052, USA
3
CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Campus Agrário de Vairão, 4169-007 Vairão, Portugal
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Viruses 2020, 12(7), 758; https://doi.org/10.3390/v12070758
Received: 28 May 2020 / Revised: 3 July 2020 / Accepted: 6 July 2020 / Published: 14 July 2020
(This article belongs to the Special Issue Computational Biology of Viruses: From Molecules to Epidemics)
Next-generation sequencing (NGS) offers a powerful opportunity to identify low-abundance, intra-host viral sequence variants, yet the focus of many bioinformatic tools on consensus sequence construction has precluded a thorough analysis of intra-host diversity. To take full advantage of the resolution of NGS data, we developed HAplotype PHylodynamics PIPEline (HAPHPIPE), an open-source tool for the de novo and reference-based assembly of viral NGS data, with both consensus sequence assembly and a focus on the quantification of intra-host variation through haplotype reconstruction. We validate and compare the consensus sequence assembly methods of HAPHPIPE to those of two alternative software packages, HyDRA and Geneious, using simulated HIV and empirical HIV, HCV, and SARS-CoV-2 datasets. Our validation methods included read mapping, genetic distance, and genetic diversity metrics. In simulated NGS data, HAPHPIPE generated pol consensus sequences significantly closer to the true consensus sequence than those produced by HyDRA and Geneious and performed comparably to Geneious for HIV gp120 sequences. Furthermore, using empirical data from multiple viruses, we demonstrate that HAPHPIPE can analyze larger sequence datasets due to its greater computational speed. Therefore, we contend that HAPHPIPE provides a more user-friendly platform for users with and without bioinformatics experience to implement current best practices for viral NGS assembly than other currently available options. View Full-Text
Keywords: bioinformatics; validation; simulation; viruses; consensus; haplotypes; HIV; HCV; SARS-CoV-2 bioinformatics; validation; simulation; viruses; consensus; haplotypes; HIV; HCV; SARS-CoV-2
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MDPI and ACS Style

Gibson, K.M.; Steiner, M.C.; Rentia, U.; Bendall, M.L.; Pérez-Losada, M.; Crandall, K.A. Validation of Variant Assembly Using HAPHPIPE with Next-Generation Sequence Data from Viruses. Viruses 2020, 12, 758. https://doi.org/10.3390/v12070758

AMA Style

Gibson KM, Steiner MC, Rentia U, Bendall ML, Pérez-Losada M, Crandall KA. Validation of Variant Assembly Using HAPHPIPE with Next-Generation Sequence Data from Viruses. Viruses. 2020; 12(7):758. https://doi.org/10.3390/v12070758

Chicago/Turabian Style

Gibson, Keylie M., Margaret C. Steiner, Uzma Rentia, Matthew L. Bendall, Marcos Pérez-Losada, and Keith A. Crandall. 2020. "Validation of Variant Assembly Using HAPHPIPE with Next-Generation Sequence Data from Viruses" Viruses 12, no. 7: 758. https://doi.org/10.3390/v12070758

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